Portal Exclusive: Here are five careers that can stand the test of AI

While AI might be a threat to many existing jobs, the healthcare, management and legal markets will always need human beings to function, writes Akshay Chaturvedi

The debate of AI taking over jobs as against being a force of good, has been a talk of the town for a while now. In 2017, McKinsey released a study that stated 30% of responsibilities in 60% of occupations can be computerised. On the other hand, in 2018, the Bank of England released a statement indicating that 80 million and 15 million jobs in the US and the UK, respectively, could be performed with the help of robots. Jerry Kaplan, a Stanford academic, said that automation is “blind to the colour of your collar”. It essentially means it will not matter if you are a market analyst or a professional dancer, automation is coming.

However, this fails to put forward the whole picture.

Another view, the more balanced one, says that automation may not trigger losses of jobs. It is something that I have personally seen happen over the last couple of years, in niche areas. Yes, the jobs that see more automation coming through would require the job description to be redefined. Yes, it will cause the need to re-skill. But the number of new opportunities that AI will open up will absorb everything and more.

There have been studies around this too. Martin Ford, author of 'Rise of the Robots: Technology and the Threat of a Jobless Future', says that jobs which “are on some level of routine, repetitive, and predictable” are the ones that are at the maximum risk of being taken over by AI. I strongly believe that this segment will be able to re-skill itself quickly, and governments all over the world are already stepping up to meet this demand.

As a species, we are better designed to focus on creative pursuits, and by taking a lot of automation out, the world will now give this luxury to more people than ever before. The future of the world is a combination of human analysis, creativity, and most importantly - empathy. It will bring data and the human touch together to bring more sound impact. Here are some examples of what this could look like across some professions:

1.
Healthcare: According to 'The Future of Employment Report', there exists 0.39% and 0.42% chance of automation in the jobs of dietitian and physician, respectively. An AI machine does not have the experience and temperament required to treat the wounded. The trust in a person supersedes advancement especially when it comes to the life of a person.

2.
Psychology: There is also a 0.3% chance of automation in the mental health and substance abuse social work industry. It is crucial to create a human bond with the patient to effectively treat them for the same. This is difficult to replicate with an AI algorithm; it will help immensely but would need that aid of humans.

3.
Legal: There are reports of over 1,00,000 jobs in the legal sector that could be polished with technology, but the most essential job of ‘presenting a case and its evaluation’ cannot be replaced today. The importance of judges and lawyers is difficult to undermine as they make the backbone of the legal system. But of course, with AI systems, they can do things far more efficiently.

4.
Management: Essentially, management jobs were created so that the efficiency of tasks could be increased. Their duties have over time evolved from being mere supervisors, into motivators, leaders, and trainers. The human bond of a superior and subordinate is necessary for the systems to prosper. An AI machine, today, cannot come close to the human aspect of management as a manager needs to interpret and hone the capability of every employee in a very ‘sensitive manner’.

5.
Political Science: Careers in Political Science are majorly involved with public appearances and problem-solving abilities. The advancement of a political leader is typically based on the perception of the public and an AI machine cannot be differentiated from one another. A political leader identifies the gaps in society and plans public policies accordingly. This is very subjective to each society and while an AI ‘can be trained for such diverse situations, and be responsible for smaller decision making’, it will still need human elements by its side to be robust.

While all of the above examples of professions (and options for future higher education) demonstrate the fact that data would need empathy, and together, will form the future, a better knowledge of data, emerging technologies, across all professions, will only help.

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